A Quantitative Multivariate Model of Human Dendritic Cell-T Helper Cell Communication

Abstract

Cell-cell communication involves a large number of molecular signals that function as words of a complex language, the grammar of which remaining mostly unknown. Here, we describe an integrative approach involving: i) protein-level measurement of multiple communication signals coupled to output responses in receiving cells; ii) mathematical modeling to uncover input-output relationships and interactions between signals. Using human dendritic cell (DC)-T helper (Th) cell communication as a model, we measured 36 DC-derived signals, and 17 Th cytokines broadly covering Th diversity, in 428 observations. We developed a data-driven computationally validated model capturing 56 already described, and 290 potentially novel mechanisms of Th cell specification. By predicting context-dependent behaviors, we demonstrated a new function for IL-12p70 as inducer of Th17 in an IL-1 signaling context. This work provides a unique resource to decipher the complex combinatorial rules governing DC-Th cell communication, and guide their manipulation for vaccine design and immunotherapies.